Table1_Machine learning models to predict 30-day mortality for critical patients with myocardial infarction: a retrospective analysis from MIMIC-IV database.pdf

Table1_Machine learning models to predict 30-day mortality for critical patients with myocardial infarction: a retrospective analysis from MIMIC-IV database.pdf

Background<p>The identification of efficient predictors for short-term mortality among patients with myocardial infarction (MI) in coronary care units (CCU) remains a challenge. This study seeks to investigate the potential of machine learning (ML) to improve risk prediction and develop a pred...

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Bibliographic Details
Main Author: Xuping Lin (19710184) (author)
Other Authors: Xi Pan (3080415) (author), Yanfang Yang (408813) (author), Wencheng Yang (3631522) (author), Xiaomeng Wang (348745) (author), Kaiwei Zou (19710187) (author), Yizhang Wang (5532749) (author), Jiaming Xiu (12529711) (author), Pei Yu (203358) (author), Jin Lu (428513) (author), Yukun Zhao (6116063) (author), Haichuan Lu (13034019) (author)
Published: 2024
Subjects:
Cardiology
Cardiology (incl. Cardiovascular Diseases)
Cardiorespiratory Medicine and Haematology not elsewhere classified
machine learning
30-day mortality
myocardial infarction
MIMIC-IV
coronary care unit
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